What are common memory leaks in Python and how can I avoid them?

What are common memory leaks in Python and how can I avoid them?

Common memory leaks in Python often occur due to circular references, large data structures, or unclosed resources. To avoid them, use weak references, manage your data structures carefully, and ensure you close files and network connections.

Can you explain how circular references cause memory leaks?

Sure! Circular references happen when two or more objects reference each other, preventing Python's garbage collector from reclaiming their memory. This can lead to memory not being freed even when the objects are no longer needed.

What tools can I use to detect memory leaks in my Python code?

You can use tools like objgraph, memory_profiler, and tracemalloc to detect memory leaks in Python. They help visualize memory usage and identify leaks.

Are there best practices to follow to prevent memory leaks?

Yes, some best practices include using context managers for file handling, avoiding global variables, and regularly profiling your code to monitor memory usage.